• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.403-417
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• 2014

Increased frequency of climate extremes is another face of climate change confronted by humans, resulting in catastrophic losses in agriculture. While climate extremes take place on many scales, impacts are experienced locally and mitigation tools are a function of local conditions. To address this, agrometeorological early warning systems must be place and location based, incorporating the climate, crop and land attributes at the appropriate scale. Existing services often lack site-specific information on adverse weather and countermeasures relevant to farming activities. Warnings on chronic long term effects of adverse weather or combined effects of two or more weather elements are seldom provided, either. This lecture discusses a field-specific early warning system implemented on a catchment scale agrometeorological service, by which volunteer farmers are provided with face-to-face disaster warnings along with relevant countermeasures. The products are based on core techniques such as scaling down of weather information to a field level and the crop specific risk assessment. Likelihood of a disaster is evaluated by the relative position of current risk on the standardized normal distribution from climatological normal year prepared for 840 catchments in South Korea. A validation study has begun with a 4-year plan for implementing an operational service in Seomjin River Basin, which accommodates over 60,000 farms and orchards. Diverse experiences obtained through this study will certainly be useful in planning and developing the nation-wide disaster early warning system for agricultural sector.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.25-48
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• 2014

Increased frequency of climate extremes is another face of climate change confronted by humans, resulting in catastrophic losses in agriculture. While climate extremes take place on many scales, impacts are experienced locally and mitigation tools are a function of local conditions. To address this, agrometeorological early warning systems must be place and location based, incorporating the climate, crop and land attributes at the appropriate scale. Existing services often lack site-specific information on adverse weather and countermeasures relevant to farming activities. Warnings on chronic long term effects of adverse weather or combined effects of two or more weather elements are seldom provided, either. This lecture discusses a field-specific early warning system implemented on a catchment scale agrometeorological service, by which volunteer farmers are provided with face-to-face disaster warnings along with relevant countermeasures. The products are based on core techniques such as scaling down of weather information to a field level and the crop specific risk assessment. Likelihood of a disaster is evaluated by the relative position of current risk on the standardized normal distribution from climatological normal year prepared for 840 catchments in South Korea. A validation study has begun with a 4-year plan for implementing an operational service in Seomjin River Basin, which accommodates over 60,000 farms and orchards. Diverse experiences obtained through this study will certainly be useful in planning and developing the nation-wide disaster early warning system for agricultural sector.

• Atmosphere
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• v.24 no.3
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• pp.445-456
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• 2014

A real-time quality control system for meteorological data (air temperature, air pressure, relative humidity, wind speed, wind direction, and precipitation) measured by an integrated meteorological sensor has been developed based on comparison of quality control procedures for meteorological data that were developed by the World Meteorological Organization and the Korea Meteorological Administration (KMA), using time series and statistical analysis of a 12-year meteorological data set observed from 2000 to 2011 at the Incheon site in Korea. The quality control system includes missing value, physical limit, step, internal consistency, persistence, and climate range tests. Flags indicating good, doubtful, erroneous, not checked, or missing values were added to the raw data after the quality control procedure. The climate range test was applied to the monthly data for air temperature and pressure, and its threshold values were modified from ${\pm}2{\sigma}$ and ${\pm}3{\sigma}$ to ${\pm}3{\sigma}$ and ${\pm}6{\sigma}$, respectively, in order to consider extreme phenomena such as heat waves and typhoons. In addition, the threshold values of the step test for air temperature, air pressure, relative humidity, and wind speed were modified to $0.7^{\circ}C$, 0.4 hPa, 5.9%, and $4.6m\;s^{-1}$, respectively, through standard deviation analysis of step difference according to their averaging period. The modified quality control system was applied to the meteorological data observed by the Weather Information Service Engine in March 2014 and exhibited improved performance compared to the KMA procedures.

• Journal of Environmental Impact Assessment
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• v.24 no.2
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• pp.134-153
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• 2015

When making urban planning, it is important to understand climate effect caused by urban structural changes. Seoul city applies UPIS(Urban Plan Information System) which provides information on urban planning scenario. Technology for analyzing climate effect resulted from urban planning needs to developed by linking urban planning scenario provided by UPIS and climate analysis model, CAS(Climate Analysis Seoul). CAS develops for analyzing urban climate conditions to provide realistic information considering local air temperature and wind flows. Quantitative analyses conducted by CAS for the production, transportation, and stagnation of cold air, wind flow and thermal conditions by incorporating GIS analysis on land cover and elevation and meteorological analysis from MetPhoMod(Meteorology and atmospheric Photochemistry Meso-scale model). In order to reflect land cover and elevation of the latest information, CAS used to highly accurate raster data (1m) sourced from LiDAR survey and KOMPSAT-2(KOrea Multi-Purpose SATellite) satellite image(4m). For more realistic representation of land surface characteristic, DSM(Digital Surface Model) and DTM(Digital Terrain Model) data used as an input data for CFD(Computational Fluid Dynamics) model. Eight inflow directions considered to investigate the change of flow pattern, wind speed according to reconstruction and change of thermal environment by connecting green area formation. Also, MetPhoMod in CAS data used to consider realistic weather condition. The result show that wind corridors change due to reconstruction. As a whole surface temperature around target area decreases due to connecting green area formation. CFD model coupled with CAS is possible to evaluate the wind corridor and heat environment before/after reconstruction and connecting green area formation. In This study, analysis of climate impact before and after created the green area, which is part of 'Connecting green network across the north and south in Seoul' plan, one of the '2020 Seoul master plan'.

• Journal of Industrial Convergence
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• v.21 no.8
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• pp.43-49
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• 2023

Since 2018, due to climate change, heat waves and cold waves have caused gradual damage to social infrastructure. Since the damage caused by cold weather has increased every year due to climate change in recent 4 years, the damage that was limited to a specific area is now appearing all over the country, and a lot of efforts are being concentrated from experts in various fields to minimize this. However, it is not easy to study real-time observation of sudden abnormal low temperature in existing studies to reflect local characteristics in discontinuously measured data. In this study, based on the weather-related data that affects the occurrence of cold-weather damage, we developed an algorithm pattern that can identify the time when abnormal cold temperatures occurred after searching for weather patterns at the time of cold-weather damage. The results of this study are expected to be of great help to the related field in that it is possible to confirm the time when the abnormal low temperature occurs due to the data generated in real time without relying on the past data.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.143-148
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• 2005

The main purpose of this study is to suggest and evaluate an operational method for assessing the potential impact of climate change on hydrologic components and water resources of regional scale river basins. The method, which uses large scale climate change information provided by a state of the art general circulation model(GCM) comprises a statistical downscaling approach and a spatially distributed hydrological model applied to a river basin located in Korea. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONU GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about $7.6\% of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern and the analysis of the duration cure shows the mean of averaged low flow is increased while the averaged wet and normal flow are decreased for the climate change.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.107-114
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• 1999

The large-scale distribution of crops Is usually determined by climate. We present the results of a climate-crop prediction based on spatial bio-physical process model approach, implemented in a GIS (Geographic Information System) environment using several regional and global agriculture-environmental databases. The model utilizes daily climate data like temperature, rainfall, solar radiation being generated stocastically by in-built model weather generator to determine the daily biomass and finally the crop yield. Crops are characterized by their specific growing period requirements, photosynthesis, respiration properties and harvesting index properties. Temperature and radiation during the growing period controls the development of each crop. The model simulates geographic/spatial distribution of climate by which a crop-growing belt can also be determined. The model takes both irrigated and non-irrigated area crop productivity into account and the potential increase in productivity by the technical means like mechanization is not considered. All the management input given at the base year 1995 was kept same for the next twenty-year changes until 2015. The simulated distributions of crops under current climatic conditions coincide largely with the current agricultural or specific crop growing regions. Simulation with assumed weather generated derived climate change scenario illustrate changes in the agricultural potential. There are large regional differences in the response across the country. The north-south and east-west regions responded differently with projected climate changes with increased and decreased productivity depending upon the crops and scenarios separately. When water was limiting or facilitating as non-irrigated and irrigated area crop-production effects of temperature rise and higher $CO_2$ levels were different depending on the crops and accordingly their production. Rise in temperature led to yield reduction in case of maize and rice whereas a gain was observed for wheat crop, doubled $CO_2$ concentration enhanced yield for all crops and their several combinations behaved differently with increase or decrease in yields. Finally, with this spatial modeling approach we succeeded in quantifying the crop productivity which may bring regional disparities under the different climatic scenarios where one region may become better off and the other may go worse off.

• Atmosphere
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• v.26 no.3
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• pp.445-459
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• 2016

Air temperature deviation (ATD) is one of major indicators to represent spatial distribution of urban heat island (UHI), which is induced from the urbanization. The purpose of this study is to evaluate the accuracy of air temperature deviation about Climate Analysis Seoul (CAS) workbench, which had developed by National Institute Meteorological Science and TU Berlin. Comparison and correlation analysis for CAS ATD including meso-scale air temperature deviation, local-scale air temperature deviation, total air temperature deviation, surface heat flux deviation, cold air production deviation among meso-scale numerical modelling variable in 'Seoul Region', micro-scale numerical modelling in 'Detail Region', and CAS workbench variable using observation data in ground stations. Comparison between night time OBS ATD and CAS ATD show that have most close values. Most of observations ($dT_{max}$ and $dT_{min}$) have highly positive ($dT_{SHP}$, $dT_{CA}$, MD, TD, $f_{BS}$, $f_{US}$, $f_{WS}$, $h_B$) and negative ($f_{VS}$, $f_{TV}$, $h_V$, Z) correlations. However, CAS workbench needs further improvement of both observational framework and analytical framework to resolve the problems; (1) night time OBS ATD of has closer values in compare with at high rise mountain area and (2) correlations are very dependable to meteorological scale.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.493-500
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• 2011

Recently, there has been an increase in the number of disaster victims locally due to climate change and a variety of frequently occurring natural disasters. The damage caused by abrupt weather change in local area by typical weather forecasting techniques is very limited and difficult. Recently local area weather monitoring system using wireless sensor network technology has been very actively studied. Thus an IEEE 802.15.4-based weather field server to measure and monitor the local weather changes was designed and developed in this study. The proposed weather field server utilizes a wireless sensor node and weather sensors to collect weather information such as temperature, humidity, illumination, dew point, barometric pressure, and water level. The integrated weather sensor board was designed to respond quickly to weather changes, and provide feedback to the server PC. Each weather information is analyzed in the server PC to establish a program to monitor and analyze the local area or the area of abrupt climate change in order to provide warning signals in case of disaster events in local.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.31 no.4
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• pp.16-23
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• 2013